Wimalasuriya, Daya Chinthana
2011-06-07T23:54:44Z
2011-06-07T23:54:44Z
2011-03
http://hdl.handle.net/1794/11216
xiii, 149 p. : ill. (some col.)
Information extraction (IE) aims to recognize and retrieve certain types of information from natural language text. For instance, an information extraction system may extract key geopolitical indicators about countries from a set of web pages while ignoring other types of information. IE has existed as a research field for a few decades, and ontology-based information extraction (OBIE) has recently emerged as one of its subfields. Here, the general idea is to use ontologies--which provide formal and explicit specifications of shared conceptualizations--to guide the information extraction process. This dissertation presents two novel directions for ontology-based information extraction in which ontologies are used to improve the information extraction process.
First, I describe how a component-based approach for information extraction can be designed through the use of ontologies in information extraction. A key idea in this approach is identifying components of information extraction systems which make extractions with respect to specific ontological concepts. These components are termed "information extractors". The component-based approach explores how information extractors as well as other types of components can be used in developing information extraction systems. This approach has the potential to make a significant contribution towards the widespread usage and commercialization of information extraction.
Second, I describe how an ontology-based information extraction system can make use of multiple ontologies. Almost all previous systems use a single ontology, although multiple ontologies are available for most domains. Using multiple ontologies in information extraction has the potential to extract more information from text and thus leads to an improvement in performance measures. The concept of information extractor, conceived in the component-based approach for information extraction, is used in designing the principles for accommodating multiple ontologies in an ontology-based information extraction system.
Committee in charge: Dr. Dejing Dou, Chair;
Dr. Arthur Farley, Member;
Dr. Michal Young, Member;
Dr. Monte Westerfield, Outside Member
en_US
University of Oregon
University of Oregon theses, Dept. of Computer and Information Science, Ph. D., 2011;
Information extraction
Ontologies (Information retrieval)
Software components
Computer science
Use of ontologies in information extraction
Thesis

Masud, Md. Raihan
2011-08-05T00:57:46Z
2011-08-05T00:57:46Z
2011-06
http://hdl.handle.net/1794/11476
xi, 51 p. : ill. (some col.)
Conducting field studies for human centric research often demands a significant amount of time and effort. Virtual Environments (VE) can be a potential alternative to reduce such requirements and help scale the field studies. However, we may experience a performance difference between (1) a virtual trial, and (2) a field trial of the same study. To learn under what circumstances a VE can successfully replace a field study and when it fails, this thesis describes a route-following experiment that compares the participants' performance between a simple VE and a field setup. The experiment results unveil that there is a significant difference in performance between a physical and a virtual setup for more challenging navigational tasks, whereas no significant difference is observed for simpler tasks. This finding encourages us to replace a less challenging field study with a simple VE, and explore the possibilities for a complex one.
Committee in charge: Dr. Stephen Fickas, Chairperson;
Dr. Christopher Wilson, Member
en_US
University of Oregon
University of Oregon theses, Dept. of Computer and Information Science, M.S., 2011;
Computer science
Error recovery
Human centric
Route following
Virtual environments
Virtual reality
Virtual Environments for Human Centric Research
Thesis